The M1 chip Macbook Air is the most recommended for data science due to its features. Upgrading Is Not An OptionĪlmost impossible to add more RAM to a Mac. Most data scientists would find this a little difficult to cope with. Mac systems do not contain HDMI ports, which might not be much of a problem for some individuals, but it does become a problem when a presentation is to be done and you’re to use a projection. The Mac system does not readily support hardware that is not from Apple, and it is relatively costly to purchase compared to a PC. There are a couple of cons, some of which are: Apple Products Are More ExpensiveĪ Mac is known to be pretty expensive, even more so is the compatibility with hardware. With all of the reasons above for why Mac is a great system for data science, it also has a flip side. Most data scientists spend long hours in front of a computer. Highly UsableĪ Mac system is user friendly. Easily transported and moved, you do not have to sit in front of a system for long hours without motion. LightweightĪ Mac system is known for its lightweight, which makes it easier to work with. Mac OS computers are also known for their highly durable and powerful Wi-Fi card. It allows a lot of tools and software, such as tableau, anaconda, and more. This is a key reason why data scientists prefer Macs. The Pros High compatibility with data science softwares Macs are highly capable machines, strong and durable. It is quite a popular fact that most data scientists prefer a Mac even with the expensive prices.Ī factor that is also considered is its compatibility with other tools used in data science. Macs are excellently built and to a degree offer more for a data scientist than a PC would. If you desire the best learning and working experience in data science, then you should go for a Mac. With windows computers, you can build your own PC, and gradually add better hardware. Mac computers do not support or allow a lot of upgrades to be carried out. Most users make plans to upgrade their systems over time. These are personal preferences that you should consider too. What system would be most appropriate for the niche you’d be exploringĪ clear picture of what you would be handling, kinds of apps, and data to process. Although, PC users need a specialized integrated developed environment to use certain data languages. Mac runs on a Linux/Unix-based OS that supports every data science language you can think of. What to consider before purchasing any of the above systems What OS is more suited to your specialty

Do i have a mac or a pc